Millimeter Wave Signal Pattern Recognition for Object Identification
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Solution Overview
Problem
Current wireless communication networks using millimeter-wave (mmW) bands face challenges in identifying and distinguishing objects blocking transmission signals, leading to inconsistent signal strength patterns, which affects user services and security applications.
Innovation Solution
The solution involves monitoring changes in signal strength patterns caused by objects moving between transmission points and receiving devices, correlating these patterns with database-stored base signal strength patterns to identify types of objects, and using this information to generate alerts or perform actions such as traffic monitoring and security responses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If millimeter-wave bands are used for transmission, then data service quality and speed are improved, but signal penetration through objects deteriorates causing inconsistent signal strength patterns
Solution Approach 1:
The system pre-establishes a database of base signal strength patterns for different object types (vehicles, pedestrians, animals, etc.) before actual object detection is needed. These patterns are collected and stored in advance, enabling rapid comparison and identification when objects block mmW signals during operation, thus maintaining reliable detection despite signal inconsistencies.
Solution Approach 2:
The system changes the approach from analyzing raw signal strength values to analyzing signal strength patterns and their changes over time. By monitoring pattern variations rather than absolute values, and comparing these variations against stored base patterns, the system achieves reliable object identification despite the inherently inconsistent nature of mmW signal penetration through different materials.
2Difficulty of detecting and measuring
If signal strength monitoring is used to identify objects, then object detection capability is improved, but measurement precision deteriorates due to inconsistent signal patterns
Solution Approach 1:
Base signal strength patterns for various object types are collected and stored in a database before actual detection operations. This preliminary action creates a reference library that enables accurate object identification during operation, compensating for the imprecision of individual signal measurements.
Solution Approach 2:
Instead of relying on single precise measurements, the system creates and compares signal strength patterns (copies of signal behavior over time) against stored base patterns. This pattern-matching approach using copies of signal characteristics enables accurate object identification even when individual measurements are imprecise or inconsistent.
3Measurement precision
If database storage of base signal strength patterns is implemented, then object identification accuracy is improved, but device complexity increases
Solution Approach 1:
The system uses a universal database structure that stores base signal strength patterns for multiple object types (vehicles, pedestrians, animals, stationary objects, etc.). This single multi-functional database serves all identification needs, avoiding the complexity of separate detection systems for different object categories and simplifying the overall device architecture.
Solution Approach 2:
The system stores simplified signal strength patterns (copies of signal behavior characteristics) rather than complex raw signal data. This copying approach reduces data complexity and storage requirements while maintaining identification accuracy, as the essential pattern information is preserved without needing to store complete raw signal datasets.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach effectively identifies objects and generates alerts or performs actions based on signal strength changes, enhancing user services like traffic monitoring and security systems by accurately determining the presence and type of objects interfering with mmW signals.
Implementation Method 1
millimeter-wave (mmW) transmission within a wireless communication network
Data Source
AI summary
Architecture and techniques for identifying types of objects based upon disruption of signal strength of millimeter-wave (mmW) transmitted signals caused by objects interfering with or blocking transmitted signals within a wireless communication network. In particular, types of objects may be identified based upon drops in signal strength due to objects moving between a transmission point and a receiving device. Based on factors including one or more of a size of an object, materials that make up the object, etc., the object causes a drop in received signal strength, thereby causing a change in a pattern of received signal strength. The changed pattern may be compared with base patterns that are correlated with a type or identity of an object in order to identify the object.